Working Paper: CEPR ID: DP15109
Authors: Davide Delle Monache; Andrea De Polis; Ivan Petrella
Abstract: We model permanent and transitory changes of the predictive density of US GDP growth. A substantial increase in downside risk to US economic growth emerges over the last 30 years, associated with the long-run growth slowdown started in the early 2000s. Conditional skewness moves procyclically, implying negatively skewed predictive densities ahead and during recessions, often anticipated by deteriorating financial conditions. Conversely, positively skewed distributions characterize expansions. The modelling framework ensures robustness to tail events, allows for both dense or sparse predictor designs, and delivers competitive out-of-sample (point, density and tail) forecasts, improving upon standard benchmarks.
Keywords: business cycle; downside risk; skewness; score driven models; financial conditions
JEL Codes: E32; E44; C53
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| downside risk to US economic growth (F69) | long-run growth slowdown (O49) |
| deteriorating financial conditions (F65) | downside risk to US economic growth (F69) |
| financial conditions (E66) | forecasting accuracy of GDP growth model (E17) |
| buildup of household debt (G51) | downside risk episodes (D81) |
| skewness of GDP growth distributions (D39) | downside risk (D81) |
| financial conditions (E66) | skewness of GDP growth (F62) |